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Claude Sonnet 4 vs Claude Sonnet 5

Compare Claude Sonnet 4 and Claude Sonnet 5 side-by-side. See how these vision models stack up in Image Captioning, OCR, Object Detection, Open Prompt, and Classification.

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AnthropicClaude Sonnet 4

Claude Sonnet 4 is deprecated and can no longer be run. Details and evals are still available on its model page.

AnthropicClaude Sonnet 5
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Claude Sonnet 4 vs Claude Sonnet 5: Overview

Claude Sonnet 4

Claude 4 Sonnet, released by Anthropic in May 2025, is the mid-tier model in the Claude 4 family, designed to balance capability, cost, and speed. It is multimodal, accepting both text and images, and extends beyond prior versions with improved “computer use” support, allowing API-driven interaction with desktop-like interfaces. By default, it supports 200,000 tokens of context, but as of August 2025, it also offers a 1 million-token context window in public beta—making it one of the most context-capable models available for processing entire codebases or large document sets in a single request.

Sonnet 4 is significantly cheaper than the flagship Opus while still demonstrating strong reasoning, coding, and instruction-following ability with reduced hallucinations. Its extended context capabilities and lower latency make it well-suited for enterprise-scale knowledge management, software development, research assistants, and productivity automation where both cost efficiency and high reliability are essential.

Claude Sonnet 5

Claude Sonnet 5 is a mid-tier large language model from Anthropic, released on June 30, 2026, as the latest model in the Sonnet series and a direct successor to Claude Sonnet 4.6. It is a hybrid reasoning model designed primarily for agentic workflows, software coding, and professional tasks. The model features a 1 million token context window, a 128k maximum output token limit, and runs adaptive thinking by default, giving API users fine-grained control over reasoning effort across five levels (low, medium, high, max, and extra-high). It uses an updated tokenizer shared with Opus 4.7 and later models, which produces approximately 30% more tokens for equivalent text compared to earlier Claude models. On benchmarks, Sonnet 5 scores 63.2% on agentic coding and 81.2% on OSWorld, narrowing the gap with Opus 4.8 while remaining at Sonnet-tier pricing.

The model supports text and image input with text output, and accepts tools including browsers and terminals for autonomous multi-step task execution. Anthropic's safety evaluations report that Sonnet 5 shows a lower rate of undesirable behaviors than Sonnet 4.6 and is generally safer in agentic contexts, with improved resistance to prompt injection and reduced sycophancy. Cybersecurity safeguards equivalent to those on Opus 4.7 and 4.8 are active, though Anthropic notes the model was not deliberately trained on cybersecurity tasks. The model is proprietary and API-only, with no open weights.

Claude Sonnet 4 vs Claude Sonnet 5 Comparison Table

PropertyClaude Sonnet 4Claude Sonnet 5
OrganizationAnthropicAnthropic
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateMay 2025Jun 2026
Context Window1.0M1.0M
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$3.00$2.00
Output $/1M$15.00$10.00
Vision Tasks
CaptioningDemo
ClassificationDemo
Object DetectionDemo
OCRDemo
Vision Language
Visual Question AnsweringDemo
Document Question Answering
Multi-Label Classification
Model Features
LLMs with Vision Capabilities
Multimodal Vision
Foundation Vision
Vision Evalspass/fail results · 67 prompts
Score key:≥75%40–74%<40%
Visual Understanding
Overall Score
68.66%
70.15%
Avg Response Time21.26s3.90s
Median input tokensincl. image tokens2.1K
Median output tokens61
Est. cost / taskon this benchmark$0.0048
Defect Detection
80%(12/15)
73.3%(11/15)
Document Understanding
88.9%(8/9)
66.7%(6/9)
Object Counting
20%(2/10)
20%(2/10)
Object Understanding
78.6%(11/14)
92.9%(13/14)
Spatial Understanding
68.4%(13/19)
78.9%(15/19)
OCR
Overall Score
83.84%
Avg Response Time2.77s
Median input tokensincl. image tokens642
Median output tokens64
Est. cost / taskon this benchmark$0.0019
Focused Scene OCR
88.9%(88/99)
Handwritten Math
50%(5/10)
License Plate Recognition
90%(27/30)
Text Recognition
80%(24/30)
VQA & Extraction
80%(48/60)

Output tokens (incl. reasoning) and est. cost / task are measured on this benchmark from a single low-temperature run, and shown only for models whose run covered at least 90% of prompts. Methodology